SOURCE-LINKED INTELLIGENCE
tcnerv:dual-domain temporal context modeling for implicit neural video compression
Video compression aims to minimize reconstruction distor tion under a constrained bit rate. Existing video implicit neural representations (INRs) often decode frames independently, leaving intermediate features unconditioned on previous reconstructions and content embeddings without explicit temporal prediction. We propose TCNeRV, which exploits reconstructed context in both feature and embedding domains. Its multi-scale temporal-context fusion (MTCF) module injects gated historical features at multiple decoder scales, while temporal embedding-residual coding (TERC) predicts each content embed
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T09:00:18.000Z
First collected: 2026-09-20T09:01:24.920Z. This is not the publication date.